This notebook contains a set of analyses for analyzing thechampz’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
thechampz | training | published before 2020 | 40 | 54 |
thechampz | validation | published 2020 | 3 | 4 |
thechampz | test | published after 2020 | 1 | 1 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.
One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.
Note: the tree below has been further pruned to make it easier to visualize.
Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.
We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | User_Collection | All_Games | Ratio |
thechampz | Stonemaier Games | 5.0% | 0.0% | 123.49 |
thechampz | Artist Klemens Franz | 15.0% | 0.6% | 25.33 |
thechampz | Variable Setup | 15.0% | 1.4% | 10.58 |
thechampz | Pegasus Spiele | 20.0% | 2.2% | 9.11 |
thechampz | Fantasy Flight Games | 10.0% | 1.2% | 8.52 |
thechampz | Map Continental National Scale | 15.0% | 1.9% | 7.74 |
thechampz | Asmodee | 20.0% | 2.6% | 7.67 |
thechampz | Open Drafting | 32.5% | 8.3% | 3.90 |
thechampz | Deduction Game | 17.5% | 5.1% | 3.43 |
thechampz | Hand Management | 50.0% | 20.2% | 2.48 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2019 | 286096 | Tapestry | 0.614 | no |
2 | 2011 | 96848 | Mage Knight Board Game | 0.505 | no |
3 | 2009 | 39683 | At the Gates of Loyang | 0.391 | no |
4 | 2014 | 163412 | Patchwork | 0.245 | yes |
5 | 2015 | 172386 | Mombasa | 0.214 | no |
6 | 2006 | 25613 | Through the Ages: A Story of Civilization | 0.200 | no |
7 | 2017 | 226320 | My Little Scythe | 0.197 | no |
8 | 2018 | 244711 | Newton | 0.185 | no |
9 | 2016 | 169786 | Scythe | 0.177 | yes |
10 | 2011 | 70919 | Takenoko | 0.167 | no |
11 | 2008 | 35677 | Le Havre | 0.143 | no |
12 | 2013 | 143693 | Glass Road | 0.133 | no |
13 | 2017 | 233078 | Twilight Imperium: Fourth Edition | 0.133 | no |
14 | 2010 | 70512 | Luna | 0.119 | no |
15 | 2010 | 39684 | Merkator | 0.102 | no |
16 | 2011 | 70149 | Ora et Labora | 0.101 | no |
17 | 2017 | 174430 | Gloomhaven | 0.096 | no |
18 | 2016 | 205418 | Agricola: Family Edition | 0.092 | no |
19 | 2013 | 133848 | Euphoria: Build a Better Dystopia | 0.082 | no |
20 | 2018 | 258036 | Between Two Castles of Mad King Ludwig | 0.080 | no |
21 | 2014 | 159508 | AquaSphere | 0.080 | no |
22 | 2015 | 178900 | Codenames | 0.075 | no |
23 | 2019 | 285984 | Last Bastion | 0.075 | no |
24 | 2019 | 266192 | Wingspan | 0.070 | no |
25 | 2016 | 177736 | A Feast for Odin | 0.069 | no |
26 | 2013 | 148000 | Sissi!: Die Bohnenkaiserin | 0.066 | no |
27 | 2015 | 182875 | Hengist | 0.066 | no |
28 | 2018 | 246639 | Patchwork Express | 0.063 | no |
29 | 2019 | 284435 | Nova Luna | 0.062 | no |
30 | 2014 | 164928 | Orléans | 0.061 | no |
31 | 2016 | 200680 | Agricola (Revised Edition) | 0.059 | yes |
32 | 2012 | 129051 | Le Havre: The Inland Port | 0.057 | no |
33 | 2016 | 193265 | Port Royal: Unterwegs! | 0.057 | no |
34 | 2017 | 220520 | Caverna: Cave vs Cave | 0.055 | no |
35 | 2017 | 216132 | Clans of Caledonia | 0.055 | no |
36 | 2013 | 146278 | Tash-Kalar: Arena of Legends | 0.054 | no |
37 | 2007 | 22827 | StarCraft: The Board Game | 0.053 | no |
38 | 2018 | 253684 | Spring Meadow | 0.053 | no |
39 | 2007 | 31260 | Agricola | 0.053 | no |
40 | 2013 | 128621 | Viticulture | 0.052 | no |
41 | 2007 | 22825 | Tide of Iron | 0.048 | no |
42 | 1997 | 11 | Bohnanza | 0.048 | yes |
43 | 2016 | 171131 | Captain Sonar | 0.047 | no |
44 | 2000 | 26055 | Twilight Imperium: Second Edition | 0.045 | no |
45 | 2014 | 156009 | Port Royal | 0.043 | no |
46 | 2017 | 224037 | Codenames: Duet | 0.043 | no |
47 | 2017 | 220774 | Codenames: Marvel | 0.042 | no |
48 | 2013 | 146418 | Warhammer: Diskwars | 0.041 | no |
49 | 2012 | 127023 | Kemet | 0.039 | no |
50 | 2018 | 241831 | Reykholt | 0.038 | no |
51 | 2016 | 205637 | Arkham Horror: The Card Game | 0.038 | no |
52 | 2018 | 249821 | Codenames: Harry Potter | 0.037 | no |
53 | 2019 | 290028 | Codenames: The Simpsons | 0.036 | no |
54 | 2017 | 162886 | Spirit Island | 0.036 | no |
55 | 2002 | 8095 | Prophecy | 0.035 | no |
56 | 2013 | 102794 | Caverna: The Cave Farmers | 0.035 | no |
57 | 2019 | 264239 | Patchwork Doodle | 0.035 | no |
58 | 2006 | 24843 | Graenaland | 0.034 | no |
59 | 2014 | 174402 | Tide of Iron: Next Wave | 0.033 | no |
60 | 2016 | 182340 | Star Trek: Frontiers | 0.033 | no |
61 | 2005 | 18833 | Lord of the Rings: The Confrontation | 0.033 | no |
62 | 1998 | 944 | Mag·Blast | 0.032 | no |
63 | 2002 | 6209 | Mag·Blast (Second Edition) | 0.032 | no |
64 | 2018 | 199792 | Everdell | 0.031 | no |
65 | 2012 | 119890 | Agricola: All Creatures Big and Small | 0.031 | yes |
66 | 2010 | 25292 | Merchants & Marauders | 0.031 | no |
67 | 2016 | 204027 | Cottage Garden | 0.031 | no |
68 | 2019 | 276025 | Maracaibo | 0.031 | no |
69 | 2017 | 234487 | Altiplano | 0.030 | no |
70 | 2002 | 4395 | Bean Trader | 0.030 | no |
71 | 2012 | 117914 | Milestones | 0.029 | no |
72 | 2015 | 163745 | Star Wars: Armada | 0.029 | no |
73 | 2019 | 270971 | Era: Medieval Age | 0.028 | no |
74 | 2009 | 31563 | Middle-Earth Quest | 0.028 | no |
75 | 2017 | 233678 | Indian Summer | 0.028 | no |
76 | 2012 | 121921 | Robinson Crusoe: Adventures on the Cursed Island | 0.028 | no |
77 | 2019 | 283863 | The Magnificent | 0.027 | no |
78 | 2019 | 272682 | Expedition to Newdale | 0.027 | no |
79 | 2018 | 245638 | Coimbra | 0.027 | yes |
80 | 1999 | 425 | Thunder's Edge | 0.026 | no |
81 | 2016 | 192836 | The Colonists | 0.026 | no |
82 | 2018 | 258444 | Gingerbread House | 0.026 | no |
83 | 1997 | 24 | Twilight Imperium | 0.026 | no |
84 | 2012 | 123260 | Suburbia | 0.025 | no |
85 | 2005 | 17223 | World of Warcraft: The Boardgame | 0.025 | no |
86 | 2001 | 5791 | Maelstrom | 0.025 | no |
87 | 2010 | 68448 | 7 Wonders | 0.025 | no |
88 | 2013 | 127024 | Room 25 | 0.025 | no |
89 | 2006 | 23142 | Mag·Blast: Third Edition | 0.025 | no |
90 | 2017 | 233676 | Noria | 0.024 | no |
91 | 2017 | 197376 | Charterstone | 0.024 | no |
92 | 2008 | 38453 | Space Alert | 0.024 | no |
93 | 2018 | 205896 | Rising Sun | 0.024 | no |
94 | 2019 | 265683 | Second Chance | 0.024 | no |
95 | 2012 | 122522 | Smash Up | 0.023 | no |
96 | 1998 | 25 | Battlemist | 0.023 | no |
97 | 2012 | 119432 | Snowdonia | 0.023 | no |
98 | 2011 | 103184 | The Gnomes of Zavandor | 0.023 | no |
99 | 2017 | 220775 | Codenames: Disney – Family Edition | 0.023 | no |
100 | 1982 | 170 | Family Business | 0.022 | no |
This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
wflow_id | .metric | .estimator | .estimate |
GLM | roc_auc | binary | 0.86 |
Decision Tree | roc_auc | binary | 0.68 |
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.
The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think thechampz is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2019 | 286096 | Tapestry | 0.614 | no |
2011 | 96848 | Mage Knight Board Game | 0.505 | no |
2009 | 39683 | At the Gates of Loyang | 0.391 | no |
2015 | 172386 | Mombasa | 0.214 | no |
2006 | 25613 | Through the Ages: A Story of Civilization | 0.200 | no |
What games does the model think thechampz is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2017 | 226518 | Exit: The Game – The Sunken Treasure | 0.001 | yes |
2000 | 822 | Carcassonne | 0.001 | yes |
2019 | 282493 | TINYforming Mars | 0.001 | yes |
2009 | 46213 | Telestrations | 0.001 | yes |
2017 | 231819 | Sonar | 0.001 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Le Havre: The Inland Port | Glass Road | Patchwork | Mombasa | Scythe | My Little Scythe | Newton | Tapestry |
2 | Kemet | Euphoria: Build a Better Dystopia | AquaSphere | Codenames | Agricola: Family Edition | Twilight Imperium: Fourth Edition | Between Two Castles of Mad King Ludwig | Last Bastion |
3 | Agricola: All Creatures Big and Small | Sissi!: Die Bohnenkaiserin | Orléans | Hengist | A Feast for Odin | Gloomhaven | Patchwork Express | Wingspan |
4 | Milestones | Tash-Kalar: Arena of Legends | Port Royal | Star Wars: Armada | Agricola (Revised Edition) | Caverna: Cave vs Cave | Spring Meadow | Nova Luna |
5 | Robinson Crusoe: Adventures on the Cursed Island | Viticulture | Tide of Iron: Next Wave | Viticulture Essential Edition | Port Royal: Unterwegs! | Clans of Caledonia | Reykholt | Codenames: The Simpsons |
6 | Suburbia | Warhammer: Diskwars | Istanbul | Oh My Goods! | Captain Sonar | Codenames: Duet | Codenames: Harry Potter | Patchwork Doodle |
7 | Snowdonia | Caverna: The Cave Farmers | King of New York | Between Two Cities | Arkham Horror: The Card Game | Codenames: Marvel | Everdell | Maracaibo |
8 | Smash Up | Room 25 | Fields of Arle | 504 | Star Trek: Frontiers | Spirit Island | Coimbra | Era: Medieval Age |
9 | Keyflower | Händler der Karibik | Start Frei | Isle of Skye: From Chieftain to King | Cottage Garden | Altiplano | Gingerbread House | The Magnificent |
10 | Il Vecchio | Bremerhaven | Five Tribes | Watson & Holmes | The Colonists | Indian Summer | Rising Sun | Expedition to Newdale |
11 | Würfel Bohnanza | BANG! The Dice Game | Flizz & Miez | The Voyages of Marco Polo | Terraforming Mars | Charterstone | Sonar Family | Second Chance |
12 | Archipelago | Legacy: The Testament of Duke de Crecy | Imperial Settlers | The King Is Dead | The Oracle of Delphi | Noria | Treasure Island | Tainted Grail: The Fall of Avalon |
13 | Taschkent | Karnickel | Familiar's Trouble | Trambahn | Black Orchestra | Codenames: Disney – Family Edition | NEOM | Clank!: Legacy – Acquisitions Incorporated |
14 | Tokaido | Palmyra | Takamatsu | Daxu | Lorenzo il Magnifico | Pendragon: The Fall of Roman Britain | The Cousins' War (Second Edition) | The Queen of Hansa |
15 | Zombicide | Lewis & Clark: The Expedition | Akrotiri | Mega Civilization | Inis | Tybor the Builder | Lords of Hellas | Tiny Towns |
16 | Wiz-War (Eighth Edition) | Cappuccino | Gaïa | Runebound (Third Edition) | Citadels | The Cousins' War | Book of Dragons | Victorian Masterminds |
17 | Terra Mystica | Petits meurtres & faits divers: au tribunal | Blocky Mountains | Risk: Europe | Star Wars: Rebellion | Sagrada | The World of SMOG: Rise of Moloch | The Lord of the Rings: Journeys in Middle-Earth |
18 | Clash of Cultures | Rococo | Dead of Winter: A Crossroads Game | Grand Austria Hotel | Bohnanza: The Duel | Semper Fidelis: Bitwa o Lwów 1918-1919 | Concordia Venus | Yukon Airways |
19 | Siberia: The Card Game | Munchkin Legends | Onirim (Second Edition) | Texas Showdown | Aeon's End | This War of Mine: The Board Game | Root | Masters of Renaissance: Lorenzo il Magnifico – The Card Game |
20 | Rex: Final Days of an Empire | Dungeon Roll | Gold Ahoy! | Raptor | Touria | Montana | Pandemic: Fall of Rome | Hellenica: Story of Greece |
21 | Yedo | City of Remnants | Sons of Anarchy: Men of Mayhem | Porta Nigra | Costa Rica | 878 Vikings: Invasions of England | Century: Eastern Wonders | Aftermath |
22 | Love Letter | Coal Baron | Black Fleet | Blood Rage | When I Dream | Bunny Kingdom | KeyForge: Call of the Archons | Orléans Stories |
23 | Carcassonne: Winter Edition | Packet Row | Carcassonne: Gold Rush | Metal Adventures | Great Western Trail | Smash Up: What Were We Thinking? | Azul: Stained Glass of Sintra | Watergate |
24 | The Manhattan Project | Smash Up: The Obligatory Cthulhu Set | Bakerspeed | Flip a Bird | Smash Up: Cease and Desist | Food Chain | Renegade | Century: A New World |
25 | Descent: Journeys in the Dark (Second Edition) | Bruxelles 1893 | Deus | Me Want Cookies! | Carcassonne: Amazonas | The Godfather: Corleone's Empire | Vengeance | Western Empires |
This is an interactive table for the model’s predictions for the training set (from resampling).
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
thechampz | owned | validation | GLM | roc_auc | 0.858 |
thechampz | owned | validation | Decision Tree | roc_auc | 0.588 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 300322 | Hallertau | 0.190 | no |
2020 | 312804 | Pendulum | 0.081 | no |
2020 | 301716 | Glasgow | 0.035 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.027 | yes |
2020 | 246900 | Eclipse: Second Dawn for the Galaxy | 0.022 | no |
2020 | 292333 | Cowboys II: Cowboys & Indians Edition | 0.020 | no |
2020 | 301032 | The March of Progress | 0.019 | no |
2020 | 325555 | Cantaloop: Book 1 – Breaking into Prison | 0.017 | no |
2020 | 300877 | New York Zoo | 0.014 | no |
2020 | 299592 | Beez | 0.013 | no |
2020 | 256317 | Guild Master | 0.012 | no |
2020 | 301030 | The Ming Voyages | 0.012 | no |
2020 | 308652 | Age of Dogfights: WW1 | 0.010 | no |
2020 | 316554 | Dune: Imperium | 0.009 | no |
2020 | 288775 | Fairy Trails | 0.009 | no |
2020 | 184267 | On Mars | 0.009 | no |
2020 | 293014 | Nidavellir | 0.009 | no |
2020 | 299179 | Chancellorsville 1863 | 0.008 | no |
2020 | 295905 | Cosmic Frog | 0.008 | no |
2020 | 256940 | Krosmaster: Blast | 0.008 | no |
2020 | 309105 | Sagani | 0.008 | no |
2020 | 294788 | Conqueror: Final Conquest | 0.007 | no |
2020 | 302723 | Forgotten Waters | 0.007 | no |
2020 | 304420 | Bonfire | 0.007 | no |
2020 | 284217 | Rush M.D. | 0.007 | no |
2020 | 302465 | Obsidia | 0.006 | no |
2020 | 319966 | The King Is Dead: Second Edition | 0.006 | no |
2020 | 306735 | Under Falling Skies | 0.006 | no |
2020 | 306481 | Tawantinsuyu: The Inca Empire | 0.006 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.006 | no |
2020 | 282922 | Windward | 0.006 | no |
2020 | 262274 | D6: Dungeons, Dudes, Dames, Danger, Dice and Dragons! | 0.006 | no |
2020 | 300010 | Dragomino | 0.005 | no |
2020 | 233262 | Tidal Blades: Heroes of the Reef | 0.005 | no |
2020 | 315196 | Dungeons & Dragons: Adventure Begins | 0.005 | no |
2020 | 312965 | Hogs of War: The Miniatures Game | 0.005 | no |
2020 | 288539 | The Jaws of Victory: Battle of Korsun-Cherkassy Pocket – January/February 1944 | 0.005 | no |
2020 | 310448 | Zombie Teenz Evolution | 0.005 | no |
2020 | 318977 | MicroMacro: Crime City | 0.005 | no |
2020 | 302524 | Super-Skill Pinball: 4-Cade | 0.005 | no |
2020 | 298018 | Memorinth | 0.005 | no |
2020 | 316750 | The Princess Bride Adventure Book Game | 0.005 | no |
2020 | 326767 | Infinity N4: Core Rules | 0.005 | no |
2020 | 299939 | Doodle Dungeon | 0.005 | no |
2020 | 284742 | Honey Buzz | 0.005 | no |
2020 | 286021 | Free Market: NYC | 0.005 | no |
2020 | 276205 | Philosophia: Dare to be Wise | 0.005 | no |
2020 | 298572 | Cosmic Encounter Duel | 0.005 | no |
2020 | 308765 | Praga Caput Regni | 0.004 | no |
2020 | 282081 | The Zorro Dice Game | 0.004 | no |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 100 upcoming games, highlighting in blue ones the user already owns.
Published | ID | Name | Pr(Owned) | Owned |
2021 | 329465 | Red Rising | 0.073 | no |
2022 | 356033 | Libertalia: Winds of Galecrest | 0.061 | no |
2021 | 343905 | Boonlake | 0.051 | no |
2021 | 305682 | Rolling Realms | 0.050 | no |
2022 | 331106 | The Witcher: Old World | 0.036 | no |
2022 | 310873 | Carnegie | 0.033 | no |
2023 | 347909 | Rogue Angels: Legacy of the Burning Suns | 0.025 | no |
2021 | 285967 | Ankh: Gods of Egypt | 0.021 | no |
2021 | 336794 | Galaxy Trucker | 0.019 | yes |
2021 | 329962 | Cantaloop: Book 2 – A Hack of a Plan | 0.018 | no |
2021 | 331635 | Kameloot | 0.018 | no |
2021 | 298378 | Maharaja | 0.014 | no |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.013 | no |
2022 | 295770 | Frosthaven | 0.013 | no |
2022 | 322524 | Bardsung | 0.012 | no |
2022 | 317511 | Tindaya | 0.012 | no |
2021 | 330036 | Great Plains | 0.012 | no |
2022 | 351605 | Bohnanza: 25th Anniversary Edition | 0.011 | no |
2022 | 314580 | Hamburg | 0.010 | no |
2021 | 330038 | Llamaland | 0.010 | no |
2021 | 338980 | Eastern Empires | 0.010 | no |
2021 | 273330 | Bloodborne: The Board Game | 0.009 | no |
2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.009 | no |
2021 | 298102 | Roll Camera!: The Filmmaking Board Game | 0.009 | no |
2022 | 305096 | Endless Winter: Paleoamericans | 0.009 | no |
2021 | 340237 | Wonder Book | 0.009 | no |
2021 | 340466 | Unfathomable | 0.009 | no |
2021 | 314491 | Meadow | 0.008 | no |
2021 | 290236 | Canvas | 0.008 | no |
2021 | 291572 | Oath: Chronicles of Empire and Exile | 0.008 | no |
2022 | 273814 | Deliverance | 0.008 | no |
2022 | 251661 | Oathsworn: Into the Deepwood | 0.008 | no |
2022 | 349793 | Age of Rome | 0.008 | no |
2021 | 347137 | Chronicles of Avel | 0.008 | no |
2021 | 298383 | Golem | 0.008 | no |
2021 | 336195 | League of Dungeoneers | 0.008 | no |
2022 | 317321 | Darkest Dungeon: The Board Game | 0.008 | no |
2021 | 277700 | Merchants Cove | 0.007 | no |
2022 | 311988 | Frostpunk: The Board Game | 0.007 | no |
2021 | 339789 | Welcome to the Moon | 0.007 | no |
2022 | 283137 | Human Punishment: The Beginning | 0.007 | no |
2021 | 299255 | Vienna Connection | 0.007 | no |
2021 | 338834 | MicroMacro: Crime City – Full House | 0.007 | no |
2021 | 348461 | Castle Break | 0.007 | no |
2021 | 304985 | Dark Ages: Holy Roman Empire | 0.007 | no |
2021 | 295535 | Dark Ages: Heritage of Charlemagne | 0.007 | no |
2021 | 297562 | Kemet: Blood and Sand | 0.007 | no |
2021 | 344277 | Corrosion | 0.007 | no |
2021 | 295785 | Euthia: Torment of Resurrection | 0.007 | no |
2021 | 249277 | Brazil: Imperial | 0.007 | no |
2021 | 319263 | One Card Dungeon | 0.006 | no |
2021 | 304324 | Dive | 0.006 | no |
2021 | 291859 | Riftforce | 0.006 | no |
2022 | 331398 | Mythic Battles: Ragnarök | 0.006 | no |
2021 | 301366 | Caves of Rwenzori | 0.006 | no |
2021 | 339906 | The Hunger | 0.006 | no |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.006 | no |
2021 | 259962 | Stress Botics | 0.006 | no |
2021 | 340909 | Gloomholdin' | 0.006 | no |
2021 | 341009 | Armonia | 0.006 | no |
2021 | 341918 | Tulpenfieber | 0.006 | no |
2021 | 332944 | Sobek: 2 Players | 0.005 | no |
2021 | 347304 | Time's Up!: Harry Potter | 0.005 | no |
2021 | 288385 | Masters of the Night | 0.005 | no |
2021 | 331549 | MiniQuest Adventures | 0.005 | no |
2023 | 274471 | Malhya: Lands of Legends | 0.005 | no |
2022 | 338067 | 6: Siege – The Board Game | 0.005 | no |
2021 | 307703 | Dawn of Battle | 0.005 | no |
2022 | 300217 | Merchants of the Dark Road | 0.005 | no |
2021 | 256680 | Return to Dark Tower | 0.005 | no |
2021 | 298069 | Cubitos | 0.005 | no |
2021 | 304336 | Million Dollar Script | 0.005 | no |
2021 | 328479 | Living Forest | 0.005 | no |
2021 | 339484 | Savannah Park | 0.005 | no |
2021 | 291847 | Mantis Falls | 0.005 | no |
2021 | 306202 | Philosophia: Floating World | 0.005 | no |
2021 | 342942 | Ark Nova | 0.005 | no |
2021 | 325348 | Successors (Fourth Edition) | 0.005 | no |
2021 | 329450 | Equinox | 0.005 | no |
2021 | 299566 | Batman: The Animated Series Adventures – Shadow of the Bat | 0.005 | no |
2022 | 280726 | Legacies | 0.005 | no |
2023 | 337627 | Voidfall | 0.005 | no |
2022 | 337098 | Lords of Vaala: Dragonbond | 0.005 | no |
2022 | 304051 | Creature Comforts | 0.005 | no |
2021 | 334782 | Bayou Bash | 0.005 | no |
2022 | 271601 | Feed the Kraken | 0.005 | no |
2022 | 311823 | Nova Aetas Renaissance | 0.005 | no |
2021 | 319792 | Fly-A-Way | 0.005 | no |
2021 | 281676 | Galactic Era | 0.005 | no |
2021 | 260524 | Beyond Humanity: Colonies | 0.005 | no |
2022 | 281258 | Sub Terra II: Inferno's Edge | 0.005 | no |
2023 | 312959 | Rallyman: DIRT | 0.005 | no |
2022 | 308028 | Drop Drive | 0.005 | no |
2022 | 340325 | Vagrantsong | 0.005 | no |
2021 | 333144 | Stronghold: Undead (Second Edition) | 0.004 | no |
2021 | 325698 | Juicy Fruits | 0.004 | no |
2021 | 315767 | Cartographers Heroes | 0.004 | no |
2021 | 326804 | Rorschach | 0.004 | no |
2022 | 347703 | First Rat | 0.004 | no |
2022 | 254127 | Europa Universalis: The Price of Power | 0.004 | no |